A major hurdle in freight demand modeling has always been a lack of adequate data on freight movements for different industry sectors for planning applications. Several data sources are available for freight planning purposes in the United States. Of these, the most commonly adopted sources include Freight Analysis Framework (FAF), Transearch (TS), American Trucking Research Institute (ATRI) truck GPS data, and Department of Transportation (DOT) weigh-in-motion (WIM) data. Of these, the two most commonly adopted commodity flow data sources are FAF and TS. We developed a fused database from FAF and TS to realize transportation network flows at a fine spatial resolution while accommodating the production and consumption behavioral trends (provided by TS). Towards this end, we formulated and estimated a joint econometric model framework embedded within a network flow approach and grounded in maximum likelihood technique to estimate county level commodity flows. Subsequently, we developed additional algorithms to disaggregate county levels flows to the statewide traffic analysis zone resolution. The second part of the project was focused on generating truck OD flows by different weight categories, including empty truck flows. The estimated empty flows (where truck load is less than a threshold) were disaggregated into finer granularity to get better understanding about the patterns associated with empty flows.
Freight Data Fusion from Multiple Data Sources for Freight Planning Applications in Florida
2018
196 pages
Report
No indication
English
Approach to Classifying Freight Data Elements across Multiple Data Sources
Transportation Research Record | 2019
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